---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-AH
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Augmented-Final
      split: train
      args: Augmented-Final
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9681397738951696
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-AH

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1143
- Accuracy: 0.9681

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9527        | 1.0   | 122  | 1.9746          | 0.1716   |
| 1.818         | 2.0   | 244  | 1.7423          | 0.3628   |
| 1.5044        | 3.0   | 366  | 1.3707          | 0.5046   |
| 1.1173        | 4.0   | 488  | 0.9796          | 0.6300   |
| 0.8714        | 5.0   | 610  | 0.7475          | 0.7379   |
| 0.8631        | 6.0   | 732  | 0.5978          | 0.7729   |
| 0.628         | 7.0   | 854  | 0.4791          | 0.8212   |
| 0.5588        | 8.0   | 976  | 0.3517          | 0.8705   |
| 0.5632        | 9.0   | 1098 | 0.2564          | 0.9168   |
| 0.3693        | 10.0  | 1220 | 0.1875          | 0.9455   |
| 0.321         | 11.0  | 1342 | 0.1525          | 0.9424   |
| 0.2761        | 12.0  | 1464 | 0.1143          | 0.9681   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3